Conventional data storage devices are highly suited to the precise storage and retrieval needs of digital computing, and have the attribute that bits of data are stored and retrieved as perfectly as possible. The data is stored in a form conducive to manipulation by a file system, a system of tables, or object associated bytes. Intelligent drives attempt to move properties of a computing system into the storage device, but do not fundamentally change the nature of permanent, non-volatile, storage devices of which the most common examples today are disc drives and flash memory devices.
It has been apparent to many researchers for scores of years that to have a practical inductive reasoning device, massive non-linear stochastic processing computation is required. This requires an enormous amount of memory or non-volatile storage space for the parameters stored in a large number of data units. There have been several successful efforts to date in scaling up to large parameter stochastic processing networks, on the order of millions of data units. Some of the efforts have employed top of the line supercomputers. But scaling up to proportions in the millions or hundreds of millions, or even billions is not yet practical.
There is a need for a storage device that performs non-linear stochastic processing computations, and can be connected to other such storage devices if further scale up is required outside the boundary of a single device.